A strategy assisted machine learning to process multi-objective optimization for improving mechanical properties of carbon steels

On the thermal and mechanical stability of reverted austenite by intercritical tempering

(2021) G. Han et al.   MATERIALS LETTERS

Enhanced carbon enrichment in austenite through introducing pre-existing austenite as a ‘carbon container’ in 0.2C-2Mn steel: The significant impact on microstructure and mechanical properties

(2021) B. Hu et al.   MATERIALS CHARACTERIZATION

Data mining to effect of key alloying elements on corrosion resistance of low alloy steels in Sanya seawater environmentAlloying Elements

(2020) Xin Wei et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning

(2020) Yue Liu et al.   ACTA MATERIALIA

Accelerated design of Fe-based soft magnetic materials using machine learning and stochastic optimization

(2020) Yuhao Wang et al.   ACTA MATERIALIA

High-throughput simulation combined machine learning search for optimum elemental composition in medium entropy alloy

(2020) Jia Li et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Accelerating materials discovery using machine learning

(2020) Yongfei Juan et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

The effect of increasing Cu and Ni on a significant enhancement of mechanical properties of high strength low alloy, low carbon steels of HSLA-100 type

(2019) A.R. Hosseini Far et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Machine learning assisted design of high entropy alloys with desired property

(2019) Cheng Wen et al.   ACTA MATERIALIA

The determining role of intercritical annealing condition on retained austenite and mechanical properties of a low carbon steel: Experimental and theoretical analysis

(2019) Z.J. Xie et al.   MATERIALS CHARACTERIZATION

Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models

(2019) Yan Zhang et al.   ACTA MATERIALIA

The austenite reversion and co-precipitation behavior of an ultra-low carbon medium manganese quenching-partitioning-tempering steel

(2018) Yu Li et al.   ACTA MATERIALIA

Data-driven evaluation of fatigue performance of additive manufactured parts using miniature specimens

(2018) H.Y. Wan et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Atom probe tomography and numerical study of austenite stabilization in a low carbon low alloy steel processed by two-step intercritical heat treatment

(2017) Z.J. Xie et al.   SCRIPTA MATERIALIA

Near-A c3 austenitized ultra-fine-grained quenching and partitioning (Q&P) steel

(2016) Lawrence Cho et al.   SCRIPTA MATERIALIA

Accelerated search for materials with targeted properties by adaptive design

(2016) Dezhen Xue et al.   Nature Communications

Enhanced ductility and toughness in an ultrahigh-strength Mn–Si–Cr–C steel: The great potential of ultrafine filmy retained austenite

(2014) Guhui Gao et al.   ACTA MATERIALIA

Effects of multiple normalizing processes on the microstructure and mechanical properties of low carbon steel weld metal with and without Nb

(2011) Shitong Wei et al.   MATERIALS & DESIGN

The conflicts between strength and toughness

(2011) Robert O. Ritchie   NATURE MATERIALS